the biophysics of neural computation

Mission: Our mission is to understand key computations that occur in sensory processing and sensorimotor integration, and to describe the mechanisms underlying these computations.

Approach: We use the brain of the fly Drosophila melanogaster to investigate these questions. This brain is relatively tractable because it contains only ~100,000 neurons. The Drosophila genetic toolbox allows us to rapidly generate new reagents to label or manipulate specific cell types. It turns out that many individual neurons are uniquely identifiable across brains, and they have fairly consistent connectivity and activity patterns. Individual neurons are also now digitally searchable, and powerful new computational neuroanatomy tools are allowing us to deduce the synaptic inputs and outputs of many individual cells. Finally, it is possible to routinely perform targeted intracellular electrophysiological recordings from identified cells in awake behaving organisms. Thus, we can study neural computations -- and their underlying mechanisms -- in fully-embodied brains. Because many neural systems in various species face the same constraints, we believe that some of the lessons we learn from this simple brain will provide clues to understanding similar problems in more complex brains.

Focus: We are currently studying several different sensory processing regions of the Drosophila brain, including olfactory and mechanosensory regions. In parallel, we are studying motor control, with a particular focus on the the brain regions that steer leg movements during walking. Our overarching goal is to develop an integrated understanding of how sequences of runs, turns, and pauses are guided by external sensory cues, internal drives, and remembered information.

Questions:

What neural computations occur at successive layers of a neural circuit?

What mechanisms implement these neural computations?

How do these particular neural computations (and their implementation) help us understand the behaviors that engage these circuits, as well as the constraints that shaped these circuits and behaviors?